Physical Sciences and Mathematics Commons^™

Enhancing Cybersecurity Based On Blockchain Technology: A Systematic Review, Sarah Mohammed Shareef, Rehab Flaih Hassan

Journal of Soft Computing and Computer Applications

Cybersecurity is a crucial component of the security system that guards against unauthorized access to digital transactions. Blockchain is a decentralized ledger used to securely exchange digital currencies and conduct trades and transactions. Blockchain technology has led to significant changes in electronic transactions. The enormous potential is being exploited in many areas such as financial services, real estate, supply chain, and the Internet of Things. Despite being a security system, it has suffered from security threats to sensitive data. Phishing and 51% attacks can circumvent blockchain security, highlighting the need for thorough user education and awareness. Additionally, blockchains based on …

Predicting Earthquake Location Using Convolutional Neural Network-Attention Mechanism Approach, Mohammed A. Jaleel Shaneen, Suhad M. Kadhem

Journal of Soft Computing and Computer Applications

In seismically active areas, earthquake prediction is essential for minimizing potential damages and preserving lives. However, precise forecasts are complicated to achieve because of seismic events’ complex and unpredictable nature. The current study presents an advanced prediction approach to address such issues, combining Convolutional Neural Networks (CNNs) and Attention Mechanism (AM). The primary goal is to improve the accuracy of the earthquake predictions and the generalizability across various mainland Chinese regions. AM layer emphasizes significant features for improving the prediction performance, whereas CNNs are utilized to extract spatial features of seismic data. The efficiency and effectiveness of the proposed approach …

Elemental Analysis Of Sediments In Johnson County, Kansas: Applications In Fluvial Suspended Sediment Tracing, Kiena Campbell

Undergraduate Theses, Capstones, and Recitals

This exploratory study investigates whether bulk elemental analysis of sediment samples using inductively coupled mass spectrometry (ICP-MS) can reveal chemical signatures that identify anthropogenic contributions to sedimentation and increased fluvial suspended sediment loads, and whether these contribution sources can be identified. Human activity, urbanization, and changes in land use increase erosion, resulting in higher-than-natural suspended sediments (SS) in waterways and increasing sedimentation in reservoirs across the state of Kansas. These threats to freshwater storage capacity are especially urgent given the projected rise in freshwater demand in the Great Plains region driven by climate change. Understanding the origin of anthropogenic SS …

Machine Learning: Neural Networking With Relu And Optimization, Aidan Redmond Brownell

Undergraduate Theses, Capstones, and Recitals

At its core, learning is an algorithmic process: it begins with input data, undergoes a series of transformations or computations, and yields an output intended to solve a specific task. This output is then compared against a target or desired result, and the internal mechanisms are updated based on how well the output aligns with expectations. While this feedback-driven process occurs almost effortlessly in humans, it is a far more structured, deliberate, and computationally intensive undertaking for machines.

Enhancing Water Scarcity Resilience In Egypt Through Machine Learning-Driven Phenological Crop Mapping And Water Use Efficiency Analysis, Surendra Maharjan, Wenzhao Li, Shahryar Fazli, Aqil Tariq, Rejoice Thomas, Cyril Rakovski, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Agriculture forms the backbone of Egypt’s economy, with the Nile Valley and Delta serving as key production zones for crops like wheat, rice, and clover. However, the sector faces mounting pressure from water scarcity, as it depends almost entirely on the Nile for irrigation, making it necessary to map major crops for assessing Water Use Efficiency (WUE) and informing agricultural planning. In this study, we used machine learning (ML) techniques—specifically Support Vector Machine (SVM) to time-series phenological data and optical indices (Enhanced Vegetation Index (EVI), Bare Soil Index (BSI), Land Surface Water Index (LSWI), Normalized Difference Vegetation Index (NDVI), and …

Evolutionary Dynamics Of Artificial Agents: Exploration And Learning In Games, Brian Mintz

Dartmouth College Ph.D Dissertations

The natural world abounds with examples of complex behavior in humans and many other species. Evolutionary game theory is a powerful mathematical framework to understand the origins of many such behaviors like cooperation. Since these behaviors are often selected against initially, understanding why they are so widespread has been a longstanding question. Rather than assuming agents' rationality, like in traditional game theory, this approach studies the mutation and selection of strategies themselves. However most behavior is neither perfectly rational nor entirely determined by genetics. This dissertation works to bridge the gap between these two perspectives by analyzing models where individuals …

Great Work Is Done While We Sleep, Julie Wildschut

University Faculty Publications and Creative Works

No abstract provided.

Evaluation Of Ecostress Collection 2 Evapotranspiration Products: Strengths And Uncertainties For Evapotranspiration Modeling, Zoe Amie Pierrat, Adam J. Purdy, Gregory Halverson, Joshua B. Fisher, Kanishka Mallick, Madeleine Pascolini-Campbell, Youngryel Rye, Martha C. Anderson, Claire Villanueva-Weeks, Margaret C. Johnson, Brenna Hatch, Evan Davis, Yun Yang, Kerry Cawse-Nicholson

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) collects thermal observations from the International Space Station to support evapotranspiration (ET) research at fine spatial resolutions (70 m × 70 m). Initial ET from ECOSTRESS Collection 1 was used in scientific research and applications, though subsequent analyses identified areas for improvement. This study outlines updates to ECOSTRESS Collection 2 ET and presents an accuracy assessment of ET and auxiliary variables validated against in situ data from AmeriFlux. Key updates in Collection 2 include use of four independent model estimates of instantaneous latent energy (LE) and improved auxiliary forcing data. …

Basic Theory And Implementations Of Quantum Error Correction, Derek Rodriguez

Undergraduate Theses, Capstones, and Recitals

The introduction of quantum computing has presented algorithmic solutions to computationally difficult challenges that are far more efficient than those of classical computers. These algorithms leverage the properties of quantum mechanics to manipulate the quantum properties of subatomic particles, requiring immense precision and stability. Current quantum hardware, however, is too noisy and introduces too many errors for these algorithms to be useful in practice, necessitating the use of error correction algorithms. This field survey seeks to introduce various principles of quantum mechanics relevant to quantum computing and quantum error correction (QEC), detail the implementation and motivations of a basic QEC …

Analyzing Human - Nonhuman Primate Conflict Mitigation Techniques In Mto Wa Mbu, Northern Tanzania, Lil Adams

Undergraduate Theses, Capstones, and Recitals

Human-wildlife conflict is a widespread challenge faced by those living in regular contact with wildlife that can have profound impacts on livelihood outcomes for humans, wildlife, and their shared environment (Barua et al., 2013; Blackie, 2023). Human – non-human primate conflict is particularly crucial due to primates’ high capacity to live among human populations (Chapman & Chapman, 1990; Alberts & Altmann, 2006; Reader et al., 2011; Sinha & Vijayakrishnan, 2017), and is currently on the rise due to increasing contact between human and non-human primates (Hockings, 2016; Uddin et al., 2020). To characterize and analyze techniques currently being used to …

Simplicial Decomposition And Realization, Matthew Ellison

Dartmouth College Ph.D Dissertations

In simplicial decomposition, we define two invariants --- V_Z and V_Q --- which represent notions of integral and rational volume of a certain class of simplicial complexes. We prove V_Z and V_Q are additive under disjoint union and connected sum, and investigate `integrality gaps' between the two quantities. We apply the theory to establish a conjecture of Sleator, Thurston, and Tarjan on tetrahedral fillings, and, as a corollary, obtain a new proof of Pournin's 2012 result on the diameter of the associahedron. In simplicial realization, we provide practical sufficient conditions and computer code to prove the existence of Euclidean embeddings …

Integrating Iota Tangle And Artificial Intelligence (Ai) In Iot Network For Network Anomaly Detection, Saida Hafsa Rafique

Thesis/ Dissertation Defenses

The Internet of Things (IoT) ecosystem has advanced with the advent of Distributed Ledger Technology (DLT) and Artificial Intelligence (AI). Individually, DLT and AI have been explored for enhancement of data management, security, integrity and efficiency of IoT systems. In this thesis, the combined use to apply DLT and AI for network anomaly detection in IoT systems is considered. A framework is proposed to integrate IOTA Tangle, a DLT architecture with Machine Learning (ML)- Random Forest, Decision Trees, and LightGBM, to detect network anomalies in IoT systems. The proposed framework processes network traffic data from UNSW-NB15 dataset and categorizes it …

Versatile Imidazole Scaffold With Potent Activity Against Multiple Apicomplexan Parasites, Monique Khim, Jemma Montgomery, Mariana Laureano De Souza, Melvin Delvillar, Lyssa J. Weible, Mayuri Prabakaran, Matthew A. Hulverson, Tyler Eck, Rammohan Y. Bheemanabonia, P. Holland Alday, David P. Rotella, J. Stone Doggett, Bart L. Staker, Kayode K. Ojo, Purnima Bhanot

Department of Chemistry and Biochemistry Faculty Scholarship and Creative Works

Malaria, toxoplasmosis, and cryptosporidiosis are caused by apicomplexan parasites Plasmodium spp., Toxoplasma gondii, and Cryptosporidium parvum, respectively, and pose major health challenges. Their therapies are inadequate, ineffective or threatened by drug resistance. The development of novel drugs against them requires innovative and resource-efficient strategies. We exploited the kinome conservation of these parasites to determine the cellular targets and effects of two Plasmodium falciparum inhibitors in T. gondii and C. parvum. The imidazoles, (R)-RY-1-165 and (R)-RY-1-185, were developed to target the cGMP dependent protein kinase of P. falciparum (PfPKG), orthologs of which are present in T. gondii and C. parvum. Using …

The Spectral Response Of Time-Resolved Piv In A Turbulent Boundary Layer, Peter Manovski, Wagih Abu Rowin, Henry Ng, Paul Gulotta, Matteo Giacobello, Charitha De Silva, Nicholas Hutchins, Ivan Marusic

Student Publications

This study presents the application of time-resolved particle image velocimetry (TR-PIV) to measure the mean and fluctuating velocity components in a turbulent boundary layer (TBL) over an axisymmetric body of revolution. A narrow wall-normal strip of the flow was captured using a synchronised high-speed laser and camera at a recording frequency of up to 80 kHz. The resulting streamwise and wall-normal velocity TR-PIV data were validated against hot-wire anemometry measurements and direct numerical simulations (DNS) of a flat plate under matched flow conditions. The mean flow results showed good agreement between all methods, while the expected attenuation due to the …

Shrinkage Study In Photopolymerisable Hybrid Sol-Gel Through Holographic Patterning, Jamshed Aftab, Izabela Naydenova, Tatsiana Mikulchyk

Articles

Photopolymerisation induced shrinkage of holographic materials is one of the main factors which needs to be considered for designing holographic optical elements (HOEs) with high accuracy in light redirection with maximum efficiency. This work studies the shrinkage in photopolymerisable hybrid sol-gel (PHSG) by examining the properties of volume transmission gratings recorded in PHSG layers. It explores both the dependence of shrinkage on the holographic grating parameters (thickness, spatial frequency, slant angle) and the effect of material aging. By using the fringe-plane rotation model, shrinkage is found to have the maximum value of 1.37 % at 765 lines/mm (19.36° slant angle) …

Multi-Label Classification Of Acoustic And Electronic Drum Sounds Using Machine Learning, Sean Perman

Electronic Theses and Dissertations

This paper presents a system for multi-class classification of drum sounds using audio signal processing and machine learning techniques. The project utilizes a diverse dataset of both acoustic and electronic drum samples and extracts ten distinct audio features to capture the timbral and temporal characteristics of each sound. The methodology includes signal preprocessing, feature extraction, and the application of supervised classification algorithms to distinguish between multiple drum classes. Experimental evaluations demonstrate that the selected features significantly enhance classification accuracy across a varied dataset. These findings underscore the effectiveness of combining traditional audio processing with modern machine learning, offering promising applications …

Enhancing Multi-Step Stock Price Forecasting With Social Media Sentiment And Engagement Metrics, Damilare Olaniyan

Electronic Theses and Dissertations

This thesis investigates whether social media sentiment can improve the accuracy of stock price prediction beyond traditional historical data. While financial markets have long relied on structured numerical indicators, the growing influence of public discourse on platforms like Twitter has introduced new opportunities for extracting market-relevant signals from unstructured text. The study focuses on four major technology firms and combines sentiment features derived from Twitter with historical stock prices in a hybrid machine learning framework. Engagement-weighted sentiment, linguistic complexity, and polarity intensity were extracted using natural language processing techniques and incorporated into classification and regression models. Results show that including …

Collaborative Federated Learning For Robots In Heterogeneous Environments, Karlan Schneider

Electronic Theses and Dissertations

This research investigates the performance of Federated Averaging (FedAvg) in simulated Federated Learning (FL) scenarios with varying degrees of environmental heterogeneity among robotic agents. The study explores the impact of data heterogeneity on both the convergence of FedAvg and the fairness of learning, with regard to consistency of performance across agents. Experiments were conducted with simulated robots trained to perform a target collection task, where a subset of agents encountered an unfamiliar environment. The results demonstrate that while FedAvg exhibits resilience to the introduction of new environmental data, it struggles to ensure both convergence and fairness in heterogeneous settings. Specifically, …

Photochemistry Of Quinones And Combustion-Derived Particles, Desiree J. Sarmiento

Electronic Theses and Dissertations

Quinones are ubiquitous species that can be produced from the photochemical aging of combustion-derived particles (CDPs). Polycyclic aromatic hydrocarbons (PAHs) are a major component of CDPs and are precursors to quinones and other oxidized products (OPAHs). My work first expanded on the PAH and OPAH photochemistry research of Dr. John Haynes, who showed that anthracene (ANT) oxidizes into 1,4-naphthoquinone (1,4-NAPQ), 1,4-anthraquinone (1,4-ANTQ), and 9,10-anthraquinone (9,10-ANTQ), and of Dr. Heather Runberg, who demonstrated the ability of ANT and these quinones to generate reactive oxygen species (ROS). Then at the Pacific Northwest National Laboratory (PNNL), I was given the opportunity to investigate …

Synthesis Of Anti-Schistosomal Heterocyclic Compounds Targeting Thioredoxin Glutathione Reductase, Alexander Stewart

Lawrence University Honors Projects

chistosomiasis is a deadly and debilitating parasitic disease caused by Schistosoma mansoni which affects 200+ million people annually who come into contact with contaminated water. Currently only one drug (Praziquantel) has been used to treat this disease for almost 50 years, and fear of resistance is growing, thus a new drug and new target is needed. Inhibition of the organism-specific redox defense protein Thioredoxin Glutathione Reductase (TGR) has lead to the death of the worm in vitro, indicating that it would be a good druggable target. Fragment based analysis and x-ray crystallography have returned the outline of a lead compound …

Study Of Agn Jet And Possible Connection Among Different Agn Classes, Shahjahan Iqbal

University Departments

No abstract provided.

Composite Magnetic Monopoles, Moreshwar Pathak

University Departments

No abstract provided.

Spin Precession In Magnetized Kerr Spacetime, Karthik Krishnamurthy Iyer

University Departments

No abstract provided.

Interacting Galaxy Clusters As A Probe To Cosmic Filaments, Shreya R. Kamath

University Departments

No abstract provided.

Photometric And Spectroscopic Properties Of Hydrogen-Rich Supernovae, Chaitrika B. M

University Departments

No abstract provided.

Simple Yet Effective, Effective Yet Inclusive: A Skincare Line, Ayesha Wali Rahimoon

Lawrence University Honors Projects

This honors project addresses the lack of inclusive skincare formulations by developing a scientifically grounded skincare line with an antioxidant-rich serum, moisturizer, and cleanser tailored to support diverse skin types, particularly melanin-rich skin. The serum combines strawberry extract powder, Manuka honey, niacinamide, green tea extract, and humectants to promote hydration, antioxidant protection, and skin barrier reinforcement. Formulated with a stable pH of 5.0–5.5 and an effective preservative system, the product was tested through non-animal, biologically relevant models.

A UV protection assay using HEK293 cells demonstrated that the serum significantly reduces oxidative damage, increasing post-exposure cell viability to 80%, compared to …

Predicting The Photophysics Of Bdpa-Based Radicals Using Density Functional Theory, Samantha Kristine Piwoni

Lawrence University Honors Projects

Through this project, computational tools were refined to be more rigorous and robust for the primarily synthetic SazLab at Lawrence University. The primary research of the SazLab involves synthesizing and characterizing luminescent radicals based on two stable radical systems: TTM and BDPA. The BDPA system is of particular interest because the effects on luminescence of its nonalternant symmetry are less understood compared to the alternant symmetry of TTM. Quantum mechanical calculations, particularly Density Functional Theory, were utilized to help target syntheses and gain insight into the photophysics of luminescence. A prior student researcher with the SazLab had successfully synthesized 2-pyBDPA, …

Optimizing Option Market Clearing, Juan Andrés Malaver Alvarado

Electronic Theses and Dissertations

Modern options markets clear each strike in isolation, leaving cross-strike arbitrage unexploited. This thesis applies a payoff-dominant clearing mechanism to realized trades—roughly 2 000 Cboe VIX option executions from June–November 2016—after classifying each trade’s side and bundling by expiration. Three optimization formulations are tested: a fractional linear program (LP), a mixed-integer LP, and a pure integer program. On a 10-core laptop every bundle solves in < 0.5 s. The LP captures the greatest surplus, yet the integer models recover nearly as much while filling whole contracts and holding only modest margin. Results reveal persistent, albeit small, inefficiencies in executed trades and demonstrate that an integral cross-strike auction could operate in real time. The accompanying C/Gurobi code is modular and readily extendable to early-exercise options. Trade-level evidence thus supports redesigning exchange clearing to consider the complete option book.

Early Diagnosis And Detection Of Skin Cancer Using Deep Neural Network Models And Feature Extraction From Pre-Trained Cnns, Sahil Khanna

Harrisburg University Dissertations and Theses

Skin cancer is one of the most common and lethal cancer types. While accurate diagnosis at an early stage is essential for skin cancer treatment it remains difficult to achieve in many regions due to lack of sufficient dermatologists and proper diagnostic equipment. Prior studies show Convolutional Neural Network (CNN) models excel at skin lesion classification and consistently achieve better results than standard diagnostic practices. However, the focus of many studies remains confined to image-based learning while neglecting useful patient metadata that could improve prediction accuracy. This research project created a specialized CNN model to classify skin lesions and evaluated …

Culture And Environment: The Calling Lakes Ecomuseum As A Community Sustainability Initiative, Kace N. Anders

Electronic Theses and Dissertations

Located in Saskatchewan, Canada, the Calling Lakes Ecomuseum, CLEM, is a community-based organization focused on water management and sustainability. Ecomuseums are holistic organizations that occupy landscapes, are responsive to community needs, conserve in situ heritage, and incorporate sustainability along with community development. The ecomuseum movement came from a need for holistic heritage management that disengaged with conventional museology and created space for communities to engage with their heritage in ways that promote community identity. This thesis analyzes the Calling Lakes Ecomuseum and how it utilizes the ecomuseum concept alongside environmental sustainability. Both semi-structured interviews and place-based field observations were used …